State-of-the-Art Fusion-Finder Algorithms Sensitivity and Specificity
Joint Authors
Carrara, Matteo
Beccuti, Marco
Lazzarato, Fulvio
Calogero, Raffaele
Cordero, Francesca
Donatelli, Susanna
Cavallo, Federica
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-02-17
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
Background.
Gene fusions arising from chromosomal translocations have been implicated in cancer.
RNA-seq has the potential to discover such rearrangements generating functional proteins (chimera/fusion).
Recently, many methods for chimeras detection have been published.
However, specificity and sensitivity of those tools were not extensively investigated in a comparative way.
Results.
We tested eight fusion-detection tools (FusionHunter, FusionMap, FusionFinder, MapSplice, deFuse, Bellerophontes, ChimeraScan, and TopHat-fusion) to detect fusion events using synthetic and real datasets encompassing chimeras.
The comparison analysis run only on synthetic data could generate misleading results since we found no counterpart on real dataset.
Furthermore, most tools report a very high number of false positive chimeras.
In particular, the most sensitive tool, ChimeraScan, reports a large number of false positives that we were able to significantly reduce by devising and applying two filters to remove fusions not supported by fusion junction-spanning reads or encompassing large intronic regions.
Conclusions.
The discordant results obtained using synthetic and real datasets suggest that synthetic datasets encompassing fusion events may not fully catch the complexity of RNA-seq experiment.
Moreover, fusion detection tools are still limited in sensitivity or specificity; thus, there is space for further improvement in the fusion-finder algorithms.
American Psychological Association (APA)
Carrara, Matteo& Beccuti, Marco& Lazzarato, Fulvio& Cavallo, Federica& Cordero, Francesca& Donatelli, Susanna…[et al.]. 2013. State-of-the-Art Fusion-Finder Algorithms Sensitivity and Specificity. BioMed Research International،Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-1030410
Modern Language Association (MLA)
Carrara, Matteo…[et al.]. State-of-the-Art Fusion-Finder Algorithms Sensitivity and Specificity. BioMed Research International No. 2013 (2013), pp.1-6.
https://search.emarefa.net/detail/BIM-1030410
American Medical Association (AMA)
Carrara, Matteo& Beccuti, Marco& Lazzarato, Fulvio& Cavallo, Federica& Cordero, Francesca& Donatelli, Susanna…[et al.]. State-of-the-Art Fusion-Finder Algorithms Sensitivity and Specificity. BioMed Research International. 2013. Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-1030410
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1030410